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metadata
license: other
license_name: mixed
license_link: https://huggingface.co/killameep/waypoint-models/blob/main/README.md
tags:
- onnx
- geolocation
- plonk
Waypoint models
ONNX exports of the networks that Waypoint runs through ONNX Runtime, an image geolocation desktop app. The app downloads these files on first launch and checks each against the SHA-256 below before using it.
These are converted copies of other people's models. Each file keeps the license of the model it
came from. The conversion changes the format only: the weights are the originals, exported with
torch.onnx by the scripts in tools/export/ of the Waypoint repository, and checked against the
PyTorch originals (see tools/parity/REPORT.md there).
License notice
streetclip_vision.onnxis licensed under CC BY-NC 4.0, inherited from StreetCLIP. Non-commercial use only. Changes: the vision tower alone, exported to ONNX, with the CLS token (before the post-layernorm) as output.- DINOv2, DISK and LightGlue files: Apache License 2.0. Changes: exported to ONNX; DINOv2's position embedding resampled to 336 px at export time; LightGlue split into one graph per stage.
- PLONK files: MIT, Copyright (c) Nicolas Dufour. Changes: one step of the Riemannian flow sampler exported to ONNX.
Because of StreetCLIP, the default model set as a whole can be used for non-commercial purposes only.
Files
| File | What | From | License | Size | SHA-256 |
|---|---|---|---|---|---|
streetclip_vision.onnx |
StreetCLIP vision tower | geolocal/StreetCLIP | CC BY-NC 4.0 | 1214.3 MB | f28cb3ff3f2ed69d43f31d8eea00498f48180c4078a09aa910ed039aba6ffa5d |
disk_unet.onnx |
DISK keypoint network | cvlab-epfl/disk (depth-save.pth) |
Apache 2.0 | 4.4 MB | 47ebf56f396249791915a101fba2f7346ea9ed36d60144b016af96c61dd7f98f |
lg_front.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 0.1 MB | 3d26471ae3f835297a27d2fa54ae9db79720e119514d76e1261bd6b2462fe483 |
lg_layer0.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | 418492373bda83d36252712f78cb1db5a1a118a8329358b4829b13f8b87f7179 |
lg_layer1.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | f6a2c9ac52cad88b15e9961829521bd1c44f43228f31a196b6cbf58d4af676eb |
lg_layer2.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | 3b0e41ee55d9b7a0ea95e884c6aeef0a0695cc96afc721383f26c63682c6f50c |
lg_layer3.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | 68c00b6bcbecb95627eb0caf9d0bd739fa706517c8ceb6d7b66b26047a3ebda8 |
lg_layer4.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | 45f11d7d36a9835ae6b3815c375f86a3bd63a06b9e332699467f0a45e7a1e37e |
lg_layer5.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | 06208eafee116630fd98bfaa8ec97742788eb77be16a2eabc7ee3dd39c0fce4e |
lg_layer6.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | ae8364c15dbb16befba2ec535258a0b618810f8b31c16d7b1e79117e270add96 |
lg_layer7.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | daa33b674cf7e50e041441213290592bb834b37240bdd17bf6dc7e88dc0a4a78 |
lg_layer8.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 5.1 MB | 169d0ca06bbc102c26b9ac1c9d62835f1c764299bd95e8f7a06249f30736d1de |
lg_post.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 0.0 MB | 8930e67cdc4d0d212a860bf80ca10bd7726d83e52f512121cdef4d1a52c045b8 |
lg_assign.onnx |
LightGlue (DISK weights), one graph of the adaptive loop | cvg/LightGlue (disk_lightglue) |
Apache 2.0 | 2.4 MB | ddace2667d842a69725c8e6112b3fd1111f42cd27b51885205ae8fcea1390880 |
plonk_osv5m_step.onnx |
PLONK OSV-5M, one flow step | nicolas-dufour/PLONK_OSV_5M | MIT | 144.3 MB | d0c5a8e14d0bf284cca9ff7d6e1074202a09c3a85b74bac77b9edd29590745d8 |
dinov2_vitl14_reg.onnx |
DINOv2 ViT-L/14 with registers | facebookresearch/dinov2 | Apache 2.0 | 1214.5 MB | a52dddb65b9b4133a10c201a2408340bab150acc738ad641f5c8d1708ca6c031 |
plonk_yfcc_step.onnx |
PLONK YFCC, one flow step | nicolas-dufour/PLONK_YFCC | MIT | 144.3 MB | 7208345304e378431462146dacc84899b95c9d3ca13f6e790842ce511dd13af7 |
plonk_inat_step.onnx |
PLONK iNaturalist, one flow step | nicolas-dufour/PLONK_iNaturalist | MIT | 36.7 MB | 04a00b7fd0db6c0aecebeb744dc39ea13be94830017bff2ddd0780317331966d |
Credits
- StreetCLIP: Haas, Alberti, Skreta. Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalization, arXiv:2302.00275.
- PLONK: Dufour, Picard, Kalogeiton, Landrieu. Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation, CVPR 2025, arXiv:2412.06781.
- DINOv2: Oquab et al. DINOv2: Learning Robust Visual Features without Supervision, arXiv:2304.07193; registers: Darcet et al., arXiv:2309.16588.
- DISK: Tyszkiewicz, Fua, Trulls. DISK: Learning local features with policy gradient, NeurIPS 2020.
- LightGlue: Lindenberger, Sarlin, Pollefeys. LightGlue: Local Feature Matching at Light Speed, ICCV 2023.